The present invention relates to an image collation apparatus and, more particularly, to an image collation method and apparatus for images such as fingerprint, noseprint, iris, and texture pattern images, and a recording medium storing an image collation program.
Various image collation apparatuses for collating images such as fingerprint, noseprint, iris, and texture pattern images have been known. For example, in the fingerprint collation apparatus disclosed in Kobayashi, “A Fingerprint Verification Method Using Thinned Image Pattern Matching”, THE TRANSACTIONS OF THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS (D-II), vol. J79-D-II, no. 3, pp. 330–340, March 1996, pattern matching is performed for fingerprint images themselves to check whether the two images are identical or different fingerprint images. FIG. 42 shows the arrangement of a fingerprint collation apparatus using such pattern matching. This fingerprint collation apparatus is comprised of an image input unit 101, image database 201, and image processing unit 305.
The image input unit 101 detects the ridges/valleys of the skin of a finger placed on a sensor by using the sensor, and performs image processing such as analog/digital conversion and binarization for a signal output from the sensor. An output from the image input unit 101 is a binary image representing a ridge of the finger skin by a pixel having a luminance corresponding to black (black pixel) and representing a valley of the finger skin by a pixel having a luminance corresponding to white (white pixel). Note that a ridge of the finger skin may be represented by a white pixel, and a valley of the finger skin may be represented by a black pixel.
The image database 201 stores fingerprint images acquired in advance as registered data. The images stored in the image database 201 will be referred to as registered images.
The image processing unit 305 collates the test image output from the image input unit 101 with the registered image output from the image database 201 to check whether the two images are identical or different fingerprint images. To improve the determination precision (collation precision), the image processing unit 305 includes an image transformation means 15, collation means 23, maximum coincidence ratio extraction means 32, and determination means 53.
The image transformation means 15 translates (shifts) and rotates each pixel of an input test image by a predetermined change amount, and outputs the resultant test image. The collation means 23 compares the luminance values of pixels at corresponding positions in the test image output from the image transformation means 15 and the registered image output from the image database 201, totals the number of pixels whose luminance values coincide with each other within a predetermined collation region, and obtains the degree or similarity (coincidence ratio) between the test image and the registered image on the basis of the totaled number of coincident pixels and the number of black pixels of the registered image. The collation means 23 also outputs a translation amount 408 to the image transformation means 15 to make the image transformation means 15 repeatedly perform translation and rotation and repeatedly perform collation by itself until the translation amount falls outside a predetermined range.
The maximum coincidence ratio extraction means 32 obtains the maximum value (maximum coincidence ratio) from the coincidence ratios output from the collation means 23 and outputs it.
The determination means 53 compares the maximum coincidence ratio with a predetermined threshold If the maximum coincidence ratio is equal to or more than the threshold, the determination means 53 determines that the two image are identical fingerprint images. If the maximum coincidence ratio is smaller than the threshold, the determination means 53 determines that the two images are different fingerprint images.
FIG. 43 shows the collating operation of the fingerprint collation apparatus in FIG. 42. First of all, the image input unit 101 detects the fingerprint of a finger placed on the sensor and generates a test image (step S51). Upon reception of the test image from the image input unit 101 (step S52) and the registered image from the image database 201 (step S53), the image processing unit 305 causes the collation means 23 to compare/collate the test image output from the image transformation means 15 with the registered image output from the image database 201 so as to obtain coincidence ratios (step S55) while causing the image transformation means 15 to translate and rotate the test image (step S54).
The image processing unit 305 then causes the maximum coincidence ratio extraction means 32 to obtain the maximum coincidence ratio from the coincidence ratios (steps S56 and S57). The image processing unit 305 repeats the above translating operation and comparison/collation until the translation amount falls outside a predetermined range (NO in step S58).
Finally, the determination means 53 of the image processing unit 305 determines that the two images are identical fingerprint images, if a maximum coincidence ratio 417 is equal to or more than the threshold (YES in step S59). If the maximum coincidence ratio 417 is smaller than the threshold, the determination means 53 determines that the two images are different fingerprint images. Note that the image processing performed by the image transformation means 15 may be performed for a registered image instead of a test image.
In the conventional fingerprint collation apparatus using pattern matching, since a maximum coincidence ratio used as a determination index is obtained from the number of coincident pixels, the ratio of the number of black pixels to the total number of pixels of each test image must be kept constant. If, for example, the ratio of the number of black pixels to the total number of pixels is set to 50%, the maximum coincidence ratio in collation between two fingerprint images acquired from different fingers (user-to-others collation) becomes about 50%. In contrast to this, the maximum coincidence ratio in collation between two fingerprint images acquired from a single finger (user-to-user collation) ideally becomes 100%. In practice, however, this ratio becomes much lower than 100% due to a positional offset or the like. As a consequence, the difference in maximum coincidence ratio between user-to-others collation and user-to-user collation becomes small. For this reason, in a conventional fingerprint collation apparatus using a maximum coincidence ratio as a determination index, it is difficult to set a threshold for determination of identical or different fingerprint images, resulting in a deterioration in collation precision. Image collation apparatus other than a fingerprint collation apparatus also suffer this problem.